Oil and gas production operations in new regions, such as the Arctic, have dramatically increased over the past few years. This increasing activity makes it more likely that fixed or floating production platforms, drill ships, and other structures will be used in these regions. A concern for these types of structures in such regions is potential for damage caused by objects that are uncontrolled and floating or submerged in the water, such as flotsam, jetsam, debris, icebergs, ice floes, and other threats (“marine obstacles”). In icy regions, for example, large icebergs and strong ice floes can pass through survey, production, and drilling areas. Although production vessels may be designed to handle some impacts from such marine obstacles, the vessels may have limits on how long impacts can be sustained and what force of potential impacts that can be handled safely.
For these reasons, operators on a production vessel or other structure will need to anticipate and defend against threats from obstacles so the production vessel can be sufficiently protected. If conditions become too dangerous, operators may also need to suspend operations and move the production vessel away until it is safe to return to normal operations. Being able to do so reliably can be of utmost importance to operators.
To monitor conditions in an icy region, operators can use iceberg drift models. Several iceberg drift models have been developed by ice engineers and scientists. Normally, the existing models are specific to a particular area of ocean. As is typical, the iceberg drift models are run onshore at data centers, and results are sent to a vessel on a daily basis or as required. This obviously requires reliable communications so data and predictions can be sent back and forth.
For example, various ice drift prediction models are available from C-Core, National Research Council of Canada (NRC), and others. Ice berg observations are obtained using airplane reconnaissance, satellite imagery, radar or manual observation, and the observations obtained offshore are sent to an onshore processing center. Then, the drift prediction model is run onshore within the processing center. Because offshore observations from vessels and the like are sent back to the processing center onshore, the drift model cannot be run if communications are down. Either way, the drift prediction model is often only run once per day in the onshore center, and the output (an image of the predicted drift for all tracked icebergs) is then sent to the vessels for review. Again, if communications are down, then sending the analysis can be hindered.
The subject matter of the present disclosure is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above.